{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as sts\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Создайте случайную величину из любого выбранного вами распределения, для разных значений n сгенерируйте 1000 выборок размера n и постройте гистрограммы средних этих выборок."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "rv = sts.norm\n",
    "sample = rv.rvs(size=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,2,100)\n",
    "pdf = rv.pdf(x)\n",
    "plt.hist(sample, density=True, bins=30, label='sample histogram')\n",
    "plt.plot(x, pdf, label='theoretical pdf', alpha=0.5)\n",
    "plt.legend()\n",
    "plt.ylabel('fraction of samples, $f(x)$')\n",
    "plt.xlabel('$x$')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Параметры запуска: размеры выборок и количество повторов генерации\n",
    "samples_sizes = (2,5,10,25,100,500,1000)\n",
    "samples_count = 1000\n",
    "\n",
    "result = []\n",
    "for sample_size in samples_sizes:\n",
    "    s_means = []\n",
    "    for number in range(samples_count):\n",
    "        # На каждом цикле генерируем выборки разных размеров\n",
    "        sample1 = rv.rvs(size=sample_size)\n",
    "        # Считаем среднее по каждой выборке и добавляем в массив средних\n",
    "        s_means.append(sample1.mean())\n",
    "    result.append((sample_size, s_means))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0ST2B64CHgQMADwVhZtZJpOk1dFcy+Ufg6GzDsbZWOenRcodgZu1cmieU/aOkuyU9lsx/XNJl2YdmZmalkOYawQzgCeCwZH4l8K2M4jEzsxJLkwh6R8SDwH8DRMR24MNMozIzs5JJkwg+kHQIhWElkDQM2JBpVGZmVjJpeg19m0JvoWMk/QnoQ+GOYDMz6wTS9BpaKOlTwMco3Cn8akRsa2IzMzPrINKMNdQFGE3hJrKuwGclsaeB5MzMrGNJ0zT0v4EtwGKSC8ZmZtZ5pEkE/SJiUOaRmJlZWaTpNfSYpM82XczMzDqiNGcELwC/k7QPhQHoBEREHJhpZGZmVhJpEsG/A6cBi/3QGDOzzidN09BfgCVOAmZmnVOaM4I1wLPJoHNbdyx091Ezs84hzRnB/wWeAboBPRq89kpSf0lzJS2XtFTSN4uUkaQpklZJWiTppOZWwMzMWifNncWTW7jv7cB3kjuTewALJD0VEcsalDkHGJC8hgJTk3czMyuRNGcELRIRayJiYTK9kcID7w9vVGwsMCsKXgAOltQ3q5jMzGx3mSWChiRVAkOAFxutOhx4o8F8HbsnCyRNkFQjqWbt2rWZxWlmlkeZJwJJBwC/Ab4VEe83Xl1kk916J0XE9IiojojqPn36ZBGmmVlupXlU5U8lHSipQtIzkt6RdFGanUuqoJAE7omI3xYpUgf0bzDfD3grzb7NzKxtpDkj+GzyS/5cCl/cxwLfbWojSQLuBpbvpavpw8AlSe+hYcCGiFiTLnQzM2sLae4jqEjeRwP3RcS7he/4Jg0HLgYWS6pNlv0LcARAREwD5iT7XQXUA5emjtzMzNpEqmGoJa0ANgNXSupDYVjqvYqI+RS/BtCwTADfSBOomZllo8mmoYiYRGGsoerkyWT1FLp9mplZJ5DmYvH+FH61T00WHQZUZxmUmZmVTpqLxb8E/g58IpmvA27MLCIzMyupNIngmIj4KYVnERARm2mi7d/MzDqONIng75L2I7nRS9IxNBiF1MzMOrY0vYZ+BDwO9Jd0D4VuoV/NMigzMyudNKOPPiVpITCMQpPQNyPincwjMzOzkthjIijybIAdd/weIemIHSOLmplZx7a3M4J/38u6AM5s41jMzKwM9pgIIuKMUgZiZmbl0eQ1AkndgSuBERTOBOYB0yKiyWEmzMys/UvTa2gWsBH4eTJ/IfAr4ItZBWVmZqWTJhF8LCJObDA/V9IrWQVkZmalleaGsv+TPCsAAElDgT9lF5KZmZVSmjOCoRQeHvN6Mn8EsFzSYgojSQ/KLDozM8tcmkRwduZRmJlZ2aS5s/ivknpSeLZw1wbLfUOZmVknkKb76E8ojC30GsnAc/iGMjOzTiNN09CXKAxF/fesgzEzs9JL02toCXBwc3cs6ReS3pa0ZA/rR0raIKk2eV3f3GOYmVnrpTkj+FcKXUiX0OA5BBFxXhPbzQBup3BD2p7Mi4hzU8RgZmYZSZMIZgI3A4uB/06744h4TlJlC+Mys2aonPRoWY67+qYxZTmuta00ieCdiJiS0fFPS+5Sfgu4JiKWFiskaQIwAeCII47IKBQzs3xKkwgWSPpX4GF2bRpqbffRhcCREbFJ0mjgIWBAsYIRMR2YDlBdXR3FypiZWcukSQRDkvdhDZa1uvtoRLzfYHqOpDsl9fbTz8zMSivNDWWZPJdA0qHA3yIiJJ1KoQfTuiyOZWZme5bmjABJY4ATgO47lkXEDU1scx8wEugtqQ74EVCRbDsNuAC4QtJ2YDMwLiLc7GNmVmJp7iyeBuwPnAHcReEL/KWmtouIC5tYfzuF7qVmZlZGaW4o+0REXAKsj4jJwGkUxh0yM7NOIE0i2Jy810s6DNgGHJVdSGZmVkpprhE8Iulg4N8odPkMCk1EZmbWCaTpNfSTZPI3kh4BukfEhmzDMjOzUmmyaUjSFyX1SGa/C/xS0pC9bWNmZh1HmmsE10XERkkjgLMojD00LduwzMysVNIkgg+T9zHA1Ij4PdAtu5DMzKyU0iSCNyX9LwoPqJkjad+U25mZWQeQ5gv9S8ATwNkR8R7Qi8K1AjMz6wTS9BqqB37bYH4NsCbLoMzMrHTcxGNmlnNOBGZmOedEYGaWc04EZmY550RgZpZzTgRmZjnnRGBmlnNOBGZmOZdZIpD0C0lvS1qyh/WSNEXSKkmLJJ2UVSxmZrZnWZ4RzADO3sv6c4AByWsCMDXDWMzMbA8ySwQR8Rzw7l6KjAVmRcELwMGS+mYVj5mZFZfmUZVZORx4o8F8XbKsU45jVDnp0XKHYGZWVDkvFqvIsihaUJogqUZSzdq1azMOy8wsX8qZCOqA/g3m+wFvFSsYEdMjojoiqvv06VOS4MzM8qKcieBh4JKk99AwYEMyxLWZmZVQZtcIJN0HjAR6S6oDfgRUAETENGAOMBpYBdQDl2YVi5mZ7VlmiSAiLmxifQDfyOr4ZmaWju8sNjPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OcK+czi82sgyvns7hX3zSmbMfubHxGYGaWc04EZmY550RgZpZzTgRmZjmXaSKQdLakVyWtkjSpyPqRkjZIqk1e12cZj5mZ7S6zXkOSugB3AKOAOuBlSQ9HxLJGRedFxLlZxWFmZnuX5RnBqcCqiPjPiPg7cD8wNsPjmZlZC2SZCA4H3mgwX5csa+w0Sa9IekzSCcV2JGmCpBpJNWvXrs0iVjOz3MoyEajIsmg0vxA4MiJOBH4OPFRsRxExPSKqI6K6T58+bRulmVnOZZkI6oD+Deb7AW81LBAR70fEpmR6DlAhqXeGMZmZWSNZJoKXgQGSjpLUDRgHPNywgKRDJSmZPjWJZ12GMZmZWSOZ9RqKiO2SrgKeALoAv4iIpZImJuunARcAV0jaDmwGxkVE4+YjMzPLUKaDziXNPXMaLZvWYPp24PYsYzAzs73zncVmZjnnRGBmlnNOBGZmOedEYGaWc04EZmY550RgZpZzuXpmcTmfr2pm1l75jMDMLOecCMzMcs6JwMws55wIzMxyzonAzCznctVryMw6j3L1Alx905iyHDdLPiMwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLOScCM7OcyzQRSDpb0quSVkmaVGS9JE1J1i+SdFKW8ZiZ2e4yu49AUhfgDmAUUAe8LOnhiFjWoNg5wIDkNRSYmrybmbVL5RzFOKt7GLI8IzgVWBUR/xkRfwfuB8Y2KjMWmBUFLwAHS+qbYUxmZtZIlncWHw680WC+jt1/7RcrcziwpmEhSROACcnsJkmvtm2oJdEbeKfcQbQB16N9cT3an8zqoptbtfmRe1qRZSJQkWXRgjJExHRgelsEVS6SaiKiutxxtJbr0b64Hu1PR6xLlk1DdUD/BvP9gLdaUMbMzDKUZSJ4GRgg6ShJ3YBxwMONyjwMXJL0HhoGbIiINY13ZGZm2cmsaSgitku6CngC6AL8IiKWSpqYrJ8GzAFGA6uAeuDSrOJpBzp001YDrkf74nq0Px2uLorYrUnezMxyxHcWm5nlnBOBmVnOORFkRFIvSU9J+kvy3rNImf6S5kpaLmmppG+WI9a9SVOPpNwvJL0taUmpY9ybzjLMSYp6HCfpeUlbJV1TjhjTSFGPf0o+h0WS/izpxHLE2ZQU9Rib1KFWUo2kEeWIM7WI8CuDF/BTYFIyPQm4uUiZvsBJyXQPYCXw8XLH3tx6JOtOB04ClpQ75gYxdQFeA44GugGvNP73pdBZ4TEK97QMA14sd9wtrMdHgFOA/wlcU+6YW1GPTwA9k+lzOvDncQD//xrsIGBFuePe28tnBNkZC8xMpmcC/6NxgYhYExELk+mNwHIKd1a3J03WAyAingPeLVFMaXWWYU6arEdEvB0RLwPbyhFgSmnq8eeIWJ/MvkDh3qL2Jk09NkWSBYB/oMiNsu2JE0F2/jGSeyKS94/srbCkSmAI8GL2oTVLs+rRzuxpCJPmlim3jhBjGs2tx2UUztbam1T1kPR5SSuAR4F/LlFsLZLlEBOdnqSngUOLrPpBM/dzAPAb4FsR8X5bxNbM47dJPdqhNhvmpMw6QoxppK6HpDMoJIL22Laedmic3wG/k3Q68BPgM1kH1lJOBK0QEXv8YCX9TVLfiFiTNDW8vYdyFRSSwD0R8duMQt2rtqhHO9VZhjnpCDGmkaoekgYBdwHnRMS6EsXWHM36PCLiOUnHSOodEe1yYD03DWXnYWB8Mj0e+H3jApIE3A0sj4hbSxhbczRZj3asswxzkqYeHUGT9ZB0BPBb4OKIWFmGGNNIU4+PJv+/SXqidQPaY1IrKPfV6s76Ag4BngH+krz3SpYfBsxJpkdQOKVcBNQmr9Hljr259Ujm76MwfPg2Cr+YLit37Elcoyn0xnoN+EGybCIwMZkWhQcovQYsBqrLHXML63Fo8u/+PvBeMn1gueNuQT3uAtY3+P9QU+6YW1iPa4GlSR2eB0aUO+a9vTzEhJlZzrlpyMws55wIzMxyzonAzCznnAjMzHLOicDMLOecCMzMcs6JwMws55wIzFopeabEqGT6RklTyh2TWXN4rCGz1vsRcIOkj1AYQfa8Msdj1iy+s9isDUj6I4WHkYyMwrMlzDoMNw2ZtZKkKgpPm9vqJGAdkROBWSskQ3PfQ+EJVR9IOqvMIZk1mxOBWQtJ2p/CkMnfiYjlFB4+8uOyBmXWAr5GYGaWcz4jMDPLOScCM7OccyIwM8s5JwIzs5xzIjAzyzknAjOznHMiMDPLuf8HD3+YVutlJz0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for sample_size, values in result:\n",
    "    # Строим графики\n",
    "    # Подписи для графиков\n",
    "    label_1 = 'sample of ' + str(sample_size) + ' histogram'\n",
    "    plt.hist(values, density=True, label=label_1)\n",
    "\n",
    "    plt.legend()\n",
    "    plt.ylabel('samples means')\n",
    "    plt.xlabel('$x$')\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
